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The association between comorbidities and self-care of heart failure: a cross-sectional study

Kyoung Suk Lee, Debra K. Moser, Kathleen Dracup

2023BMC Cardiovascular Disorders16 citationsDOIOpen Access PDF

Abstract

BACKGROUND: Because heart failure (HF) is a debilitating chronic cardiac condition and increases with age, most patients with HF experience a broad range of coexisting chronic morbidities. Comorbidities present challenges for patients with HF to successfully perform self-care, but it is unknown what types and number of comorbidities influence HF patients' self-care. The purpose of this study was to explore whether the number of cardiovascular and non-cardiovascular conditions are associated with HF self-care. METHODS: Secondary data analysis was performed with 590 patients with HF. The number of cardiovascular and non-cardiovascular conditions was calculated using the list of conditions in the Charlson Comorbidity Index. Self-care was measured with the European HF self-care behavior scale. Multivariable linear regression was performed to explore the relationship between the types and number of comorbidities and self-care. RESULTS: Univariate analysis revealed that a greater number of non-cardiovascular comorbidities was associated with poorer HF self-care(β=-0.103), but not of more cardiovascular comorbidities. In the multivariate analysis, this relationship disappeared after adjusting for covariates. Perceived control and depressive symptoms were associated with HF self-care. CONCLUSION: The significant relationship between the number of non-cardiovascular comorbidities and HF self-care was not independent of perceived control and depressive symptoms. This result suggests a possible mediating effect of perceived control and depressive symptoms on the relationship between HF self-care and the number and type of comorbidities.

Topics & Concepts

MedicineComorbidityHeart failureAngiologyMultivariate analysisInternal medicineCross-sectional studyBayesian multivariate linear regressionUnivariate analysisMultivariate statisticsPhysical therapyRegression analysisPathologyMachine learningComputer scienceMathematicsStatisticsHeart Failure Treatment and ManagementDiabetes Management and EducationCardiac Health and Mental Health
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